Multi-objective optimization of campus microgrid system considering electric vehicle charging load integrated to power grid

The increasing use of renewable energy sources and electric vehicles (EVs) has necessitated changes in the design of microgrids. In order to improve the efficiency and stability of renewable energy sources and energy security in microgrids, this paper proposes an optimal campus microgrid design that includes EV charging load prediction and a constant power support strategy from the main grid. The problem of load variation due to changes in the number of EVs connected to the microgrid will occur, and this paper presents a detailed prediction method and effective solutions. The load profile of EVs connected to the microgrid is simulated using the Monte Carlo (MC) method, taking into account EV owners’ usage habits, including charging options and dwell time, as well as battery parameters, including state of charge (SOC) and size. The simulation results show that the peak-to-valley difference in grid power after adding EVs is close to 14 times due to the uniformity of travel between staff and students. Based on how long EVs stay in the parking place, a charging and discharging policy for participation in grid dispatch is developed, which has reduced the gap between the peak and the valley. This paper gives precedence here for the main grid to provide constant power support, which would limit the electricity consumption of the campus, reduce the dependence on the main grid and moreover increase the utilization of renewable energy by the microgrid. The ideal solution set for this microgrid system model's best configuration is found using the NSGA-II optimization algorithm. To select the most suitable option, the TOPSIS method is employed. The simulation results show that the microgrid system can operate with EV integration in an economical and stable manner. Additionally, the peak-to-valley value and CO₂ emissions are reasonably reduced, and the income of EV users is increased. At the same time, the microgrid operator's charging fee for EVs can lower operating costs and also suggests that future microgrid electricity sales will be more accessible and transparent.